{"id":"W133506345","doi":"10.1007/978-3-642-27901-0_11","title":"Secret Key Establishment over Noisy Channels","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Randomness; Key (lock); Computer science; Channel (broadcasting); Computer security; Key generation; Pre-shared key; Theoretical computer science; Computer network; Cryptography; Public-key cryptography; Key distribution; Mathematics; Statistics; Encryption","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005021917,0.0004289842,0.0003919659,0.0005631329,0.00009510216,0.0002358081,0.001673493,0.0003640816,0.0001421406],"category_scores_gemma":[0.00002354754,0.0004400803,0.00008412277,0.0002655925,0.0003344329,0.0004331247,0.0006773009,0.0009154404,0.00004770061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003995945,"about_ca_system_score_gemma":0.00007200356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001814564,"about_ca_topic_score_gemma":0.0000369853,"domain_scores_codex":[0.9980177,0.00001633277,0.0003720967,0.0004696973,0.0005983035,0.0005258704],"domain_scores_gemma":[0.9981269,0.0001901285,0.00009526157,0.001339415,0.0001006709,0.0001476132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005882256,0.00005397128,0.0001378228,0.0002619268,0.00004755911,0.00002688873,0.00469409,0.1088919,0.001325619,0.02279849,0.0008251045,0.8609307],"study_design_scores_gemma":[0.000436827,0.0001288495,0.0002930997,0.001534658,0.00003354961,0.0000671688,5.026876e-7,0.6895444,0.02845406,0.1001928,0.1765957,0.002718378],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003550468,0.002425439,0.9847165,0.0001588759,0.001301255,0.0003657181,0.00001265854,0.0007334306,0.009931104],"genre_scores_gemma":[0.8642474,0.0008086939,0.1329982,0.0006983576,0.0008550934,0.00003628536,0.00003315878,0.0001337861,0.0001890104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8638924,"threshold_uncertainty_score":0.9998051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01550740546021849,"score_gpt":0.2384791400087874,"score_spread":0.2229717345485689,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}